The ability to tell time, predict the movement of other animals, and decode complex temporal patterns- such as those in speech-are among the brain's primary functions. As such, we would put forth that it will not be possible to understand the fundamental principles underlying brain function without understanding how the brain tells time and processes temporal information. We have proposed that precisely because timing is such a fundamental component to brain function that neural circuits in general are capable of processing temporal information-that is, timing does not rely on specialized or centralized circuits. This theory posits that timing emerges from the neural dynamics of recurrent neural circuits, and predicts that even neural circuits in vitro may be able to learn to tell time. We hae recently provided evidence that timing is a general computation of cortical networks. Specifically, by chronically exposing slices in the incubator to patterned stimuli (mimicking sensory experience) we have shown that the neural dynamics reproduces the temporal features of the experienced stimuli. Here we will use novel electrical and optogenetic methods to demonstrate that cortical circuits in vitro can learn temporal patterns, and elucidate the underlying neural mechanisms of timing and cortical computations. We propose that studying network-level forms of learning in reduced preparations is necessary to understand cortical computations because of the limitations of in vivo studies. Additionally, the ability to study network behavior and `learning' in vitro will provide a means to study pathological circuit level computations using tissue from animal models of cognitive disorders.